scholarly journals A nomogram for predicting overall survival in patients with Merkel cell carcinoma: A population-based analysis

2021 ◽  
Author(s):  
Miao Wang ◽  
Ye Qiu ◽  
Fang Tang ◽  
Yi-Xin Liu ◽  
Yi Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Staging System ◽  
Merkel Cell ◽  
Cox Regression Analysis

Abstract Background: Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with increasing incidence and poor prognosis. We sought to develop and validate a nomogram to estimate overall survival (OS) of MCC patients. Methods: 1863 MCC patients between 2010-2015 from the Surveillance, Epidemiology and End Results (SEER) database were randomly divided into the training and validation cohort. Independent prognostic factors determined by Cox regression analysis in the training cohort were used to establish a nomogram. We evaluated prognostic performance using the concordance index (C-index), area under receiver operating characteristic curve (AUC) and calibration curves. Decision curve analysis (DCA), net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compared the the nomogram’s clinical utility with that of the staging system.Results: eight independent prognostic factors were incorporated in the nomogram. The C-index of the nomogram was 0.744, which was superior to the C-index of AJCC TNM Stage (0.659). The AUC was greater than 0.75 and the calibration plots of this model exhibited good performance. Additionally, the positive NRI and IDI of nomogram versus the staging system illustrated that the nomogram had better predictive accuracy than the staging system (P<0.001) and the DCA showed great clinical usefulness of the nomogram. MCC patients were perfectly classified into three risk groups by the nomogram, showing better discrimination than the staging system.Conclusions: We developed and validated a nomogram to assist clinicians in evaluating prognosis of MCC patients.

scholarly journals Detection and Characterization of Circulating Tumor Cells in Patients with Merkel Cell Carcinoma

2019 ◽  
Vol 65 (3) ◽  
pp. 462-472 ◽  
Author(s):  
Sabine Riethdorf ◽  
Lina Hildebrandt ◽  
Lucie Heinzerling ◽  
Ellen Heitzer ◽  
Nicole Fischer ◽  
...  
Keyword(s):  
Overall Survival ◽  
Cell Carcinoma ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Merkel Cell Carcinoma ◽  
Cox Regression ◽  
Merkel Cell ◽  
Blood Draw ◽  
Cox Regression Analysis

Abstract BACKGROUND Merkel cell carcinoma (MCC) is a rare, aggressive skin cancer with increasing incidence and high mortality rates. MCC has recently become the subject of immune checkpoint therapy, but reliable biomarkers for estimating prognosis, risk stratification, and prediction of response are missing. METHODS Circulating tumor cells (CTCs) were detected in peripheral blood from patients with MCC by use of the CellSearch® system. Moreover, CTCs of selected cases were characterized for Merkel cell polyomavirus (MCPyV), chromosomal aberrations, and programed death ligand 1 (PD-L1) production. RESULTS Fifty-one patients were tested at first blood draw (baseline), and 16 patients had 2 or 3 consecutive measurements to detect CTCs. At baseline, ≥1 CTC (range, 1–790), &gt;1, or ≥5 CTCs/7.5 mL were detected in 21 (41%), 17 (33%), and 6 (12%) patients, respectively. After a median follow-up of 21.1 months for 50 patients, detection of CTCs correlated with overall survival (≥1, P = 0.030; &gt;1, P &lt; 0.020; and ≥5 CTCs/7.5 mL, P &lt; 0.0001). In multivariate Cox regression analysis, the detection of ≥5 CTCs/7.5 mL adjusted to age and sex compared to that of &lt;5 was associated with a reduced overall survival (P = 0.001, hazard ratio = 17.8; 95% CI, 4.0–93.0). MCPyV DNA and genomic aberrations frequently found in MCC tissues could also be detected in single CTCs. Analyzed CTCs were PD-L1 negative or only weakly positive. CONCLUSIONS The presence of CTCs is a prognostic factor of impaired clinical outcome, with the potential to monitor the progression of the disease in real time. Molecular characterization of CTCs might provide new insights into the biology of MCC.

scholarly journals A nomogram predicting overall survival in patients with non-metastatic pancreatic head adenocarcinoma after surgery: a population-based study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenbo Zou ◽  
Zizheng Wang ◽  
Fei Wang ◽  
Gong Zhang ◽  
Rong Liu
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Pancreatic Head ◽  
Staging System ◽  
Seer Database ◽  
Cox Regression Analysis ◽  
Net Reclassification Improvement ◽  
Calibration Curves

Abstract Background Pancreatic head adenocarcinoma (PHAC), a malignant tumour, has a very poor prognosis, and the existing prognostic tools lack good predictive power. This study aimed to develop a better nomogram to predict overall survival after resection of non-metastatic PHAC. Methods Patients with non-metastatic PHAC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided randomly into training and validation cohorts at a ratio of 7:3. Cox regression analysis was used to screen prognostic factors and construct the nomogram. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the performance of the model. The predictive accuracy and clinical benefits of the nomogram were validated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results From 2010 to 2016, 6419 patients with non-metastatic PHAC who underwent surgery were collected from the SEER database. A model including T stage, N stage, grade, radiotherapy, and chemotherapy was constructed. The concordance index of the nomogram was 0.676, and the AUCs of the model assessing survival at multiple timepoints within 60 months were significantly higher than those of the American Joint Committee on Cancer (AJCC) 8th staging system in the training cohort. Calibration curves showed that the nomogram had ability to predict the actual survival. The NRI, IDI, and DCA curves also indicated that our nomogram had higher predictive capability and clinical utility than the AJCC staging system. Conclusions Our nomogram has an ability to predict overall survival after resection of non-metastatic PHAC and includes prognostic factors that are easy to obtain in clinical practice. It would help assist clinicians to conduct personalized medicine.

scholarly journals Analysis of Prognostic Factors from 9387 Merkel Cell Carcinoma Cases Forms the Basis for the New 8th Edition AJCC Staging System

2016 ◽  
Vol 23 (11) ◽  
pp. 3564-3571 ◽  
Author(s):  
Kelly L. Harms ◽  
Mark A. Healy ◽  
Paul Nghiem ◽  
Arthur J. Sober ◽  
Timothy M. Johnson ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Staging System ◽  
Merkel Cell ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
8Th Edition

scholarly journals Merkel Cell Carcinoma: Changing Practice Patterns and Impact on Recurrence-Free and Overall Survival at a Single Institution and Nationally

2021 ◽  
Author(s):  
Andrew Esposito ◽  
Daniel Jacobs ◽  
Stephan Ariyan ◽  
Anjela Galan ◽  
Harriet Kluger ◽  
...  
Keyword(s):  
Overall Survival ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Practice Patterns ◽  
Cox Regression ◽  
Unknown Primary ◽  
Merkel Cell ◽  
Single Institution ◽  
Factors Associated ◽  
Changing Practice

Abstract Background Merkel cell carcinoma (MCC) is an aggressive neuroendocrine carcinoma of the skin. Our report describes the evolution of management and characteristics associated with recurrence, disease-specific survival (DSS) and overall survival (OS) in the treatment of MCC. Methods A single institution retrospective review of MCC and SEER data to determine factors associated with RFS, DSS, and OS using a multivariable Cox regression on inverse-probability weighted cohorts. Results One hundred fifty-nine patients were identified with a median age of 75. Of these, 96% were Caucasian and 60% male. Fifty-eight out of 159 (36%) of all patients were deceased with 21/58 (36%) dead from MCC with a median follow-up of 3.1 years. Institutionally, trends over time demonstrated an increased use of immunotherapy with a concomitant decrease in chemotherapy and decreased use of radiotherapy alone. Institutionally and nationally, there has been increased surgical nodal staging. Institutionally, factors associated with shorter DSS included advanced age, active cigarette smoker (p = 0.002), cT2 disease (p = 0.007), and MCC with unknown primary (p < 0.001). Institutionally, factors associated with shorter OS included ages ≥ 75 years (p < 0.001), an immunocompromised state (p < 0.001), truncal primary site (p = 0.002), and cT2 disease (HR 9.59, p < 0.001). Conclusion Changing practice patterns in MCC management have been driven by the adoption of immunotherapy. Our study highlights that competing risks of mortality in MCC patients likely prevents OS from being an accurate surrogate outcome measure to understand factors associated with DSS.

scholarly journals A novel model with nutrition-related parameters for predicting overall survival of cancer patients

2021 ◽  
Author(s):  
Qi Zhang ◽  
Kangping Zhang ◽  
Xiangrui Li ◽  
Xi Zhang ◽  
Mengmeng Song ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Nutritional Status ◽  
Cancer Patients ◽  
Cox Regression ◽  
Validation Cohort ◽  
Staging System ◽  
Tnm Staging ◽  
Cox Regression Analysis ◽  
Tnm Staging System

Abstract Background Increasing evidence indicates that nutritional status could influence the survival of cancer patients. This study aims to develop and validate a nomogram with nutrition-related parameters for predicting the overall survival of cancer patients.Patients and Methods 8,749 patients from the multicentre cohort study in China were included as the primary cohort to develop the nomogram, and 696 of these patients were recruited as a validation cohort. Patients nutritional status were assessed using the PG-SGA. LASSO regression models and Cox regression analysis were used for factor selection and nomogram development. The nomogram was then evaluated for its effectiveness in discrimination, calibration, and clinical usefulness by the C-index, calibration curves, and Decision Curve Analysis. Kaplan-Meier survival curves were used to compare the survival rate.Results Seven independent prognostic factors were identified and integrated into the nomogram. The C-index was 0.73 (95% CI, 0.72 to 0.74) and 0.77 (95% CI, 0.74 to 0.81) for the primary cohort and validation cohort, which were both higher than 0.59 (95% CI, 0.58 to 0.61) of the TNM staging system. DCA demonstrated that the nomogram was higher than the TNM staging system and the TNM staging system combined with PG-SGA. Significantly median overall survival differences were found by stratifying patients into different risk groups (score <18.5 and ≥18.5) for each TNM category (all Ps < 0.001).Conclusion Our study screened out seven independent prognostic factors and successfully generated an easy-to-use nomogram, validated and shown a better predictive validity for the overall survival of cancer patients.

scholarly journals Overall survival in patients with metastatic pancreatic cancer after surgically primary tumor resected: a SEER-based nomogram analysis

2020 ◽  
Author(s):  
Maoen Pan ◽  
Yuanyuan Yang ◽  
Xiaoting Wu ◽  
Heguang Huang
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Primary Tumor ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Tumor Resection ◽  
Training Group ◽  
Metastatic Pancreatic Cancer ◽  
Cox Regression Analysis

Abstract Background This study aimed to establish and validate a nomogram to predict overall survival in patients with metastatic pancreatic cancer (mPC) after surgically primary tumor resected. Methods All mPC patients who underwent primary tumor resection at SEER database between 2004 and 2016 were identified. We randomly assigned two-thirds of the patients to the training group and one third to the validation group. In the training group, the Kaplan–Meier survival analysis was used to analyze survival outcomes. A univariate and multivariate cox regression analysis was used to identify significant prognostic factors for establishing a nomogram. The predictive accuracy and discriminative ability were measured by the concordance index (C-index) and risk group stratification. Results A total of 742 patients were included for analysis. Four significant prognostic factors were obtained and included in the nomogram. The nomogram showed an acceptable discrimination ability (C- index:0.711) and good calibration and was further validated in the validation cohort (C- index: 0.727). The nomogram total points (NTP) had the potential to stratify patients into 2-risk groups with a median OS of 11 and 4.5 months (P < 0.001), respectively. Conclusions The nomogram can provide considerable accuracy individual prediction OS outcomes in patients with metastatic pancreatic cancer undergone primary tumor surgery and it can guide clinicians to make decisions in the clinical therapies.

Merkel Cell Carcinoma of the Skin

2000 ◽  
Vol 4 (4) ◽  
pp. 186-195 ◽  
Author(s):  
Patricia TH Tai ◽  
Edward Yu ◽  
Jon Tonita ◽  
James Gilchrist
Keyword(s):  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Primary Tumour ◽  
Staging System ◽  
Disease Status ◽  
Cancer Center ◽  
Merkel Cell ◽  
Distant Disease ◽  
Primary Disease

Background: Neuroendocrine/Merkel cell carcinoma (MCC) of the skin is an uncommon tumour. Currently, there are only limited data available on the natural history, prognostic factors, and patient management of MCC. Objective: To review our experience and build the largest database from the literature. Methods: Twenty-eight cases from the London Regional Cancer Center were combined with 633 cases obtained from the literature searched in English, French, German, and Chinese for the years 1966 to 1998. The database included age, sex, initial disease status at presentation to the clinic, site of primary, any coexisting disease, any previous irradiation, sizes of primary/nodal/distant metastases, management details, and final disease status. A new modified staging system was used: stage Ia (primary disease only, size < 2 cm), stage Ib (primary disease only, size > 2 cm); stage II (regional nodal disease), and stage III (beyond regional nodes and/or distant disease). Results: Age > 65 years, male sex, size of primary > 2 cm, truncal site, nodal/distant disease at presentation, and duration of disease before presentation (< 3 months) were poor prognostic factors. Surgery was the initial treatment of choice and it significantly improved overall survival (p = .004). Conclusion: We identified poor prognostic factors that may necessitate more aggressive treatment. The suggested staging system, incorporating primary tumour size, accurately predicted outcomes.

Prognostic nomogram to predict overall survival for patients with perihilar cholangiocarcinoma: A population-based study of SEER database (Preprint)

2020 ◽  
Author(s):  
Chendong Wang
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Staging System ◽  
Tnm Staging ◽  
Survival Outcome ◽  
Perihilar Cholangiocarcinoma ◽  
Cox Regression Analysis ◽  
Calibration Curves ◽  
Tnm Staging System ◽  
Net Benefits

BACKGROUND Perihilar cholangiocarcinoma (pCCA) is a highly aggressive malignancy with poor prognosis. Accurate prediction is of great significance for patients’ survival outcome. OBJECTIVE The present study aimed to propose a prognostic nomogram for predicting the overall survival (OS) for patients with pCCA. METHODS We conducted a retrospective analysis in a total of 940 patients enrolled from the Surveillance, Epidemiology, and End Results (SEER) program and developed a nomogram based on the prognostic factors identified from the cox regression analysis. Concordance index (C-index), risk group stratification and calibration curves were adopted to test the discrimination and calibration ability of the nomogram with bootstrap method. Decision curves were also plotted to evaluate net benefits in clinical use against TNM staging system. RESULTS On the basis of multivariate analysis, five independent prognostic factors including age, summary stage, surgery, chemotherapy, together with radiation were selected and entered into the nomogram model. The C-index of the model was significantly higher than TNM system in the training set (0.703 vs 0.572, P<0.001), which was also proved in the validation set (0.718 vs 0.588, P<0.001). The calibration curves for 1-, 2-, and 3-year OS probabilities exhibited good agreements between the nomogram-predicted and the actual observation. Decision curves displayed that the nomogram obtained more net benefits than TNM staging system in clinical context. The OS curves of two distinct risk groups stratified by nomogram-predicted survival outcome illustrated statistical difference. CONCLUSIONS We established and validated an easy-to-use prognostic nomogram, which can provide more accurate individualized prediction and assistance in decision making for pCCA patients.

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